Perbandingan Performa Pre-Trained Classifier dLib dan HAAR Cascade (OpenCV) Untuk Mendeteksi Wajah

Abstract

Face detection is a part of Computer Vision and subsection of the detection of objects. Computer Vision is defined as the branch of science that studies how the computer can recognize an object. Face detection is not yet implemented on the learning environment. Currently, the attendace process is still using paper and cheating can occur.  In this final project will compare the two pre-trained classifier applied to the learning environment by using datasets IBAtS. Two pre-trained classifier to compare performance is haar cascade and dlib. To find the best classifier then two classifier evaluation is done in order to better compareable. From the results of the evaluations already carried out have been inferred that haar cascade is a good classifier for applied learning environment.